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Saros MCP Server

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Saros MCP Server

Model Context Protocol (MCP) Server for Saros DeFi - Exposes Saros SDK functionality as AI-accessible tools

License: MIT Node.js Version

Overview

This project implements a Model Context Protocol (MCP) server that wraps the Saros DeFi SDK, enabling AI agents, bots, and dashboards to interact with Saros liquidity pools, farms, and analytics through natural language or simple tool calls.

Related MCP server: Solana MCP Server

Features

Core MCP Tools

  • get_lp_positions - Retrieve all liquidity pool positions for a wallet

  • simulate_rebalance - Simulate LP rebalancing based on IL threshold

  • portfolio_analytics - Comprehensive portfolio metrics and risk assessment

  • get_farm_positions - View farming positions and claimable rewards

  • swap_quote - Get swap quotes with price impact and slippage

Demo Clients

  • Test Client - Command-line testing tool

  • Telegram Bot - Interactive bot for portfolio management

Quick Start

Installation

cd saros-mcp-server
npm install

Running the Server

# Start the MCP server
npm start

# Development mode with auto-reload
npm run dev

Testing

# Run the test client
npm test

Usage Examples

Using with Claude Desktop

Add to your Claude Desktop MCP settings:

{
  "mcpServers": {
    "saros": {
      "command": "node",
      "args": ["/path/to/saros-mcp-server/src/index.js"]
    }
  }
}

Then in Claude:

"Show me my LP positions for wallet HqB8Rf76fAwmd4qZpL81yB2SSLFzEgdoPwpWAUJ31ont"

"Analyze my portfolio for wallet HqB8Rf76fAwmd4qZpL81yB2SSLFzEgdoPwpWAUJ31ont"

"Get me a swap quote for 100 tokens from C98A4nkJXhpVZNAZdHUA95RpTF3T4whtQubL3YobiUX9 to EPjFWdd5AufqSSqeM2qN1xzybapC8G4wEGGkZwyTDt1v in pool 2wUvdZA8ZsY714Y5wUL9fkFmupJGGwzui2N74zqJWgty"

Real Working Example:

Wallet with actual LP positions: HqB8Rf76fAwmd4qZpL81yB2SSLFzEgdoPwpWAUJ31ont (5 active positions)

Known Saros Pools:

  • C98/USDC Pool: 2wUvdZA8ZsY714Y5wUL9fkFmupJGGwzui2N74zqJWgty

Using with the Telegram Bot

  1. Create a bot via @BotFather

  2. Copy your bot token

  3. Set environment variable:

export BOT_TOKEN="your_telegram_bot_token"

  1. Run the bot:

node examples/telegram-bot.js

  1. Chat with your bot:

/start
/wallet 5UrM9csUEDBeBqMZTuuZyHRNhbRW4vQ1MgKJDrKU1U2v
/positions
/rebalance 5
/analytics

Programmatic Usage

import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";

const transport = new StdioClientTransport({
  command: "node",
  args: ["src/index.js"],
});

const client = new Client({
  name: "my-client",
  version: "1.0.0",
}, {
  capabilities: {},
});

await client.connect(transport);

// Call tools
const result = await client.callTool({
  name: "get_lp_positions",
  arguments: { wallet: "5UrM9csUEDBeBqMZTuuZyHRNhbRW4vQ1MgKJDrKU1U2v" },
});

console.log(result.content[0].text);

Project Structure

saros-mcp-server/
├── src/
│   ├── index.js                 # Main MCP server
│   ├── services/
│   │   ├── pool-service.js      # LP pool operations
│   │   ├── farm-service.js      # Farming operations
│   │   └── analytics-service.js # Analytics & IL calculations
│   └── tools/
│       ├── get-lp-positions.js
│       ├── simulate-rebalance.js
│       ├── portfolio-analytics.js
│       ├── get-farm-positions.js
│       └── swap-quote.js
├── examples/
│   ├── test-client.js           # Test client
│   └── telegram-bot.js          # Telegram bot demo
├── package.json
└── README.md

API Reference

get_lp_positions

Get all liquidity pool positions for a wallet.

Input:

{
  "wallet": "string (Solana address)"
}

Output:

Found 2 LP position(s) for wallet: 5UrM9c...

Position 1:
- Pool: 2wUvdZ...
- LP Balance: 150.5
- Token 0: C98A4n...
- Token 1: EPjFWd...

simulate_rebalance

Simulate rebalancing strategy based on impermanent loss threshold.

Input:

{
  "wallet": "string",
  "threshold": "number (0-100)"
}

Output:

Rebalance Simulation for 5UrM9c...

IL Threshold: 5%
Positions Analyzed: 2
Recommendations: 1

1. Pool: 2wUvdZ...
   - Current IL: 6.25%
   - Severity: medium
   - Action: Consider withdrawing - high IL detected

portfolio_analytics

Get comprehensive portfolio analytics.

Input:

{
  "wallet": "string"
}

Output:

Portfolio Analytics for 5UrM9c...

Overview:
- Total Positions: 2
- Estimated Total Value: $1,250.00
- Average IL: 3.5%

Risk Assessment:
✅ Low Risk - Portfolio is performing well

get_farm_positions

Get all farming/staking positions.

Input:

{
  "wallet": "string"
}

Output:

Farm Positions for 5UrM9c...

Total Farms: 1

Position 1:
- Farm: FW9hgA...
- LP Token: HVUeNV...
- Staked Amount: 100.0
- Pending Rewards:
  • 50.5 C98

swap_quote

Get swap quote with price impact.

Input:

{
  "poolAddress": "string",
  "fromMint": "string",
  "toMint": "string",
  "amount": "number",
  "slippage": "number (optional, default 0.5)"
}

Output:

Swap Quote

Input:
- Pool: 2wUvdZ...
- Amount: 100

Output:
- Expected Output: 150.5
- Minimum Output: 149.75
- Price Impact: 0.15%
- Slippage Tolerance: 0.5%

Architecture

MCP Server Layer

  • Handles MCP protocol communication

  • Exposes tools via stdio transport

  • Routes requests to service layer

Service Layer

  • PoolService: LP positions, pool info, swap quotes

  • FarmService: Staking positions, rewards

  • AnalyticsService: IL calculations, portfolio metrics

SDK Integration

  • Uses @saros-finance/sdk for Solana/Saros interactions

  • Wraps SDK functions with error handling

  • Formats data for AI-friendly consumption

Development

Adding New Tools

  1. Create tool handler in src/tools/:

export async function myNewTool(args, services) {
  const { param1, param2 } = args;

  // Tool logic here

  return {
    content: [{
      type: "text",
      text: "Result text"
    }]
  };
}

  1. Register in src/index.js:

// In ListToolsRequestSchema handler
{
  name: "my_new_tool",
  description: "Tool description",
  inputSchema: { /* schema */ }
}

// In CallToolRequestSchema handler
case "my_new_tool":
  return await myNewTool(args, this.services);

Testing

# Test with example wallet
node examples/test-client.js

# Manual testing
echo '{"jsonrpc":"2.0","method":"tools/list","id":1}' | node src/index.js

Deployment

Local Deployment

npm start

Railway/Render

  1. Create new service

  2. Connect GitHub repo

  3. Set build command: npm install

  4. Set start command: npm start

Docker (Optional)

FROM node:18
WORKDIR /app
COPY package*.json ./
RUN npm install
COPY . .
CMD ["npm", "start"]

Roadmap

  • Add DLMM-specific features (advanced orders, dynamic fees)

  • Implement real-time price feeds

  • Add transaction execution tools

  • Multi-wallet management

  • Historical performance tracking

  • Web dashboard UI

Contributing

Contributions welcome! Please:

  1. Fork the repo

  2. Create a feature branch

  3. Commit changes

  4. Submit a PR

License

MIT License - see LICENSE file

Hackathon Submission

Project: Saros MCP Server Category: SDK Usage & Developer Tools Hackathon: Saros $100K Hackathon

Key Innovations

  • First MCP server for Saros DeFi

  • AI-native portfolio management

  • Natural language DeFi interactions

  • Foundation for autonomous trading agents

Demo

  • Test Client: npm test

  • Telegram Bot: See examples/telegram-bot.js

  • Video Walkthrough: [Link TBD]

Resources

Support

Built with ❤️ for the Saros Hackathon

Available Tools

5 tools
get_farm_positionsC

Get all farming positions and staking rewards for a wallet. Shows staked LP tokens and claimable rewards.

ParametersJSON Schema
NameRequiredDescriptionDefault
walletYesSolana wallet address

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions what data is retrieved (farming positions, staked LP tokens, claimable rewards) but lacks critical details such as whether this is a read-only operation, potential rate limits, authentication requirements, or error handling for invalid wallets.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately concise with two sentences that directly state the tool's function and outputs. It's front-loaded with the main purpose, though it could be slightly more structured by separating scope details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (retrieving multiple data types for a wallet), no annotations, and no output schema, the description is minimally adequate. It specifies what data is returned but lacks details on format, pagination, or error cases, leaving gaps for the agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with the 'wallet' parameter clearly documented as a 'Solana wallet address'. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get all farming positions and staking rewards for a wallet' specifies the verb (get) and resource (farming positions and staking rewards). It distinguishes from sibling tools like 'get_lp_positions' by including staking rewards, but doesn't explicitly contrast with 'portfolio_analytics' or 'simulate_rebalance'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention sibling tools like 'get_lp_positions' (which might focus only on LP tokens) or 'portfolio_analytics' (which could offer broader analysis), leaving the agent without explicit usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_lp_positionsB

Get all liquidity pool positions for a wallet address. Returns pool details, token balances, and LP token amounts.

ParametersJSON Schema
NameRequiredDescriptionDefault
walletYesSolana wallet address (base58 encoded)

TDQS

B3.3/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool retrieves data ('Get all...') but lacks details on permissions, rate limits, error handling, or whether it's a read-only operation. The description implies it's a query but doesn't explicitly confirm safety or constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences with zero waste: the first states the purpose and input, the second specifies the return data. It's front-loaded with the core functionality and efficiently structured without unnecessary details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (single parameter, no output schema, no annotations), the description is adequate but has gaps. It covers the purpose and return values but lacks usage context, behavioral details, and output structure, making it minimally viable but incomplete for optimal agent understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents the single parameter 'wallet' as a Solana address. The description adds no additional parameter semantics beyond what's in the schema, such as format examples or validation rules, meeting the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Get all liquidity pool positions') and resource ('for a wallet address'), with explicit mention of what data is returned ('pool details, token balances, and LP token amounts'). It distinguishes from siblings like 'get_farm_positions' by focusing on liquidity pools rather than farms.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'portfolio_analytics' or 'simulate_rebalance'. It mentions what the tool does but offers no context about appropriate scenarios, prerequisites, or exclusions for usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

portfolio_analyticsC

Get comprehensive portfolio analytics including total value, IL metrics, yield performance, and position breakdown.

ParametersJSON Schema
NameRequiredDescriptionDefault
walletYesSolana wallet address

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool as a read operation ('Get'), implying it's likely safe and non-destructive, but fails to mention critical aspects like whether it requires authentication, has rate limits, or what the return format looks like. This leaves significant gaps in understanding the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded, consisting of a single sentence that efficiently states the tool's purpose and key metrics. There is no wasted verbiage, making it easy to parse, though it could be slightly more structured by explicitly separating different aspects of the analytics.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (providing comprehensive analytics) and lack of annotations and output schema, the description is moderately complete. It outlines what metrics are included but does not detail the return format, error conditions, or dependencies. This is adequate for a basic understanding but leaves gaps that could hinder effective use by an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with the 'wallet' parameter clearly documented as a 'Solana wallet address'. The description adds no additional meaning beyond this, as it does not explain how the wallet parameter influences the analytics or provide any extra context. Baseline score of 3 is appropriate since the schema adequately covers the parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('Get comprehensive portfolio analytics') and resources ('portfolio'), listing key metrics like total value, IL metrics, yield performance, and position breakdown. However, it does not explicitly distinguish this tool from sibling tools like 'get_farm_positions' or 'get_lp_positions', which might also provide position-related data, leaving some ambiguity in differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It lacks explicit context, exclusions, or references to sibling tools, such as how it differs from 'get_farm_positions' or 'simulate_rebalance', leaving the agent without clear usage instructions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

simulate_rebalanceC

Simulate rebalancing LP positions based on impermanent loss threshold. Provides recommendations for position adjustments.

ParametersJSON Schema
NameRequiredDescriptionDefault
walletYesSolana wallet address
thresholdYesIL threshold percentage (e.g., 5 for 5%)

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'simulate' and 'provides recommendations,' which implies a read-only, non-destructive operation, but does not confirm this or detail other traits like rate limits, authentication needs, or what the recommendations entail (e.g., format, scope). This leaves significant gaps for a tool with potential financial implications.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two sentences that directly state the purpose and outcome. It is front-loaded with the core action and avoids unnecessary details. However, it could be slightly more structured by explicitly separating simulation from recommendation aspects.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of financial simulation and lack of annotations or output schema, the description is incomplete. It does not explain what the recommendations include (e.g., specific adjustments, risk assessment), how results are returned, or any limitations. For a tool with no structured output and behavioral gaps, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with clear descriptions for both parameters (wallet as Solana address, threshold as IL percentage with range). The description adds no additional meaning beyond the schema, such as explaining how the threshold influences the simulation or what the wallet address is used for. Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Simulate rebalancing LP positions based on impermanent loss threshold' with the specific action 'Provides recommendations for position adjustments.' It distinguishes from siblings like get_farm_positions (which likely retrieves data) and swap_quote (which provides quotes), but could be more explicit about how it differs from portfolio_analytics in terms of simulation vs. analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention when to prefer simulate_rebalance over portfolio_analytics for analysis or get_lp_positions for data retrieval, nor does it specify prerequisites or exclusions. Usage is implied by the purpose but not explicitly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

swap_quoteC

Get swap quote for token exchange including price impact, fees, and minimum output amount with slippage.

ParametersJSON Schema
NameRequiredDescriptionDefault
poolAddressYesPool address for the swap
fromMintYesSource token mint address
toMintYesDestination token mint address
amountYesAmount to swap (in token decimals)
slippageNoSlippage tolerance (0-100, default 0.5)

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the quote includes 'price impact, fees, and minimum output amount with slippage' which gives some output context, but doesn't describe whether this is a read-only operation, potential rate limits, authentication requirements, or what happens if parameters are invalid. For a financial tool with no annotations, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose and includes key output details. Every word earns its place with no redundancy or unnecessary elaboration. It's appropriately sized for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a financial swap quote tool with no annotations and no output schema, the description is incomplete. It mentions what the quote includes but doesn't explain the return format, error conditions, or important behavioral aspects like whether this is a simulation or requires blockchain interaction. The 100% schema coverage helps, but the overall context remains inadequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 5 parameters thoroughly. The description adds minimal value beyond the schema by mentioning 'slippage' in the context of the quote output, but doesn't provide additional parameter semantics. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get swap quote for token exchange' specifies the verb (get) and resource (swap quote). It distinguishes from siblings by focusing on swap quotes rather than positions, analytics, or rebalancing. However, it doesn't explicitly differentiate from hypothetical alternative quote tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, when-not-to-use scenarios, or compare with other tools. The context signals show siblings like get_farm_positions and simulate_rebalance, but the description offers no comparative guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 5 tool updates
    • First observedget_farm_positions
    • First observedget_lp_positions
    • First observedportfolio_analytics
    • First observedsimulate_rebalance
    • First observedswap_quote
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TDQS

B3.4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap: get_farm_positions focuses on staking rewards, get_lp_positions on liquidity pool details, portfolio_analytics on overall analytics, simulate_rebalance on rebalancing simulations, and swap_quote on swap quotes. The descriptions reinforce these unique functions, making misselection unlikely.

Naming Consistency4/5

The naming is mostly consistent with a verb_noun pattern (e.g., get_farm_positions, simulate_rebalance), but there is one deviation: portfolio_analytics uses a noun_noun structure instead of a verb. This minor inconsistency does not significantly hinder readability or predictability.

Tool Count5/5

With 5 tools, the server is well-scoped for DeFi portfolio management, covering key operations like position retrieval, analytics, simulations, and swaps. Each tool earns its place without feeling excessive or insufficient for the domain.

Completeness4/5

The tool set covers core DeFi portfolio workflows comprehensively, including monitoring (get_farm_positions, get_lp_positions), analysis (portfolio_analytics), planning (simulate_rebalance), and execution (swap_quote). A minor gap exists in direct execution tools (e.g., execute_swap or stake_tokens), but agents can work around this using the provided tools.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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